The Future of Patient Education: AI-Driven Guide for Type 2 Diabetes

Introduction and aim The surging incidence of type 2 diabetes has become a growing concern for the healthcare sector. This chronic ailment, characterized by its complex blend of genetic and lifestyle determinants, has witnessed a notable increase in recent times, exerting substantial pressure on healthcare resources. As more individuals turn to online platforms for health guidance and embrace the utilization of Chat Generative Pre-trained Transformer (ChatGPT; San Francisco, CA: OpenAI), a text-generating AI (TGAI), to get insights into their well-being, evaluating its effectiveness and reliability becomes crucial. This research primarily aimed to evaluate the correctness of TGAI responses to type 2 diabetes (T2DM) inquiries via ChatGPT. Furthermore, this study aimed to examine the consistency of TGAI in addressing common queries on T2DM complications for patient education. Material and methods Questions on T2DM were formulated by experienced physicians and screened by research personnel before querying ChatGPT. Each question was posed thrice, and the collected answers were summarized. Responses were then sorted into three distinct categories as follows: (a) appropriate, (b) inappropriate, and (c) unreliable by two seasoned physicians. In instances of differing opinions, a third physician was consulted to achieve consensus. Results From the initial set of 110 T2DM questions, 40 were dismissed by experts for relevance, resulting in a final count of 70. An overwhelming 98.5% of the AI's answers were judged as appropriate, thus underscoring its reliability over traditional online search engines. Nonetheless, a 1.5% rate of inappropriate responses underlines the importance of ongoing AI improvements and strict adherence to medical protocols. Conclusion TGAI provides medical information of high quality and reliability. This study underscores TGAI's impressive effectiveness in delivering reliable information about T2DM, with 98.5% of responses aligning with the standard of care. These results hold promise for integrating AI platforms as supplementary tools to enhance patient education and outcomes.


Introduction
Type 2 diabetes mellitus (T2DM) is a global epidemic affecting approximately 9.3% of the world's population and has an all-cause mortality of 8.5% [1,2].Managing T2DM in the modern era poses a unique set of challenges stemming from the evolving lifestyle patterns, technological advancements, and the complex nature of the disease itself [3,4].In recent years, patients have been increasingly relying on medical information accessed through online search engines with nearly 80% of adults in the United States having used online resources for health-related information [5].
Chat Generative Pre-trained Transformer (ChatGPT; San Francisco, CA: OpenAI), a text-generating artificial intelligence (TGAI) with an advanced language model developed by OpenAI (ChatGPT version 3.5, August 2023, large language model, https://chat.openai.com),has been gaining growing popularity among patients to interactable respond to queries and generate human-like conversational responses, in particular for health-related information [6,7].
The primary objective of this study was to assess the accuracy of TGAI in answering questions related to T2DM and associated complications, addressing the fundamentals and frequently asked questions by patients regarding diagnosis, prevention, and the management of this global health concern.The secondary objective was to review the reproducibility of TGAI in answering frequently asked questions related to complications of T2DM, as part of a patient-education tool.

Materials And Methods
An initial set of questions about T2DM and its complications were generated by physicians experienced in treating type 2 diabetes.Subsequently, these questions underwent a thorough evaluation by research staff proficient in diabetes management prior to presentation to TGAI.ChatGPT was selected as the choice of TGAI due to its popularity and accessibility by the general public.Each question was introduced to ChatGPT three times, and the responses were recorded.Two study staff reviewed the three sets of responses to each question and summarized the majority response (Table 1).Yes, type 2 diabetes can cause frequent urination, a condition known as polyuria.When a person has type 2 diabetes, their body either becomes resistant to insulin or does not produce enough insulin.As a result, glucose cannot enter the body's cells effectively, leading to high blood glucose levels.The elevated blood glucose levels in type 2 diabetes can cause the kidneys to work harder to filter and remove the excess glucose from the blood.The kidneys excrete the excess glucose into the urine, resulting in increased urine production.This, in turn, leads to more frequent urination.
Polyuria is a common symptom of type 2 diabetes, often accompanied by increased thirst (polydipsia) and dehydration due to the loss of fluid through urine.If you are experiencing frequent urination, along with other symptoms like increased thirst, unexplained weight loss, fatigue, or blurred vision, it is important to consult with a healthcare professional for proper evaluation, diagnosis, and management of type 2 diabetes.

Trial 3
Yes, type 2 diabetes can cause frequent urination.When a person has type 2 diabetes, their body becomes resistant to the effects of insulin or doesn't use insulin effectively.As a result, glucose builds up in the bloodstream, leading to high blood glucose levels.When blood glucose levels are elevated, the kidneys attempt to filter and remove the excess glucose from the blood.This process leads to increased urine production, causing frequent urination.Frequent urination, known as polyuria, is a common symptom of diabetes.It occurs as the body tries to eliminate the excess glucose through urine.Polyuria is often accompanied by increased thirst (polydipsia) and can contribute to dehydration if fluid intake is not sufficient.If you are experiencing frequent urination, along with other symptoms like increased thirst, unexplained weight loss, fatigue, or blurred vision, it is important to consult with a healthcare professional for evaluation and proper diagnosis.They can provide appropriate management and help control blood glucose levels effectively.

TABLE 1: Examples of ChatGPT responses over three trials and summarization.
ChatGPT: Chat Generative Pre-trained Transformer Responses were reviewed by two board-certified internal medicine physicians with five and 11 years of experience and were categorized into three classes using a similar classification used in the recent literature [8].The three categories were defined as follows: (a) appropriate -provides accurate information that meets the standard of care, (b) inappropriate -answers that convey correct information but either incomplete or outdated, and (c) unreliable -the response provides inconsistent content that does not meet the standard of care.In case of a disagreement between the two physicians, a third board-certified internal medicine physician was consulted for consensus review.

Results
Of the 110 questions that were initially proposed, 52.4% (40/110) were excluded after undergoing primary review regarding relevancy by physicians experienced in the field.The remaining 63.6% (70/110) of the questions were comprised of the final dataset, of which 98.5% (69/70) of the answers were categorized as appropriate, indicating that the AI model provided accurate information meeting the standard of care for type 2 diabetes management and its associated complications (Table 2).On the other hand, 1.4% (1/70) of the responses were deemed inappropriate, containing errors but still meeting the minimal standard of care in addressing the questions (Figure 1).

Question Grade
Can   ChatGPT: Chat Generative Pre-trained Transformer

Discussion
While primarily focusing on T2DM, this study was conducted in line with ongoing efforts to uncover the potential usefulness of the TGAI as a patient-education tool.Considering the prevalence of T2DM as a major public health concern, particularly in light of the widespread dependence of patients on online resources for health-related information, this study was both timely and relevant [8,9].
Indeed, the majority of responses (98.6%) by far were appropriate, which aligns closely with the findings of previous studies conducted by Haver et  ), which appears to be a common trend among using TGAI as a source of medical information [11].This appears to be a significantly more reliable tool when compared to the reliance of patients on using search engines for medical information, as prior studies conducted by Birru et al. showed a significantly lower response accuracy of 33.3% [12].Another study that was carried out by Bremner et al. also demonstrated a diminished accuracy of 42% when online search engines were used for obtaining information by patients [13].
It's paramount to understand that while the majority of information may be accurate, the margins wherein inaccuracies exist can be potential pitfalls.Especially in the medical realm, even minimal misinformation can lead to misconceptions, which might inadvertently affect medical decisions [14].Hence, while TGAI holds promise in the context of T2DM education, users should approach it with informed caution, ideally corroborating the information with licensed medical professionals [15].
While its quality is currently not thoroughly studied, it is possible that language models may evolve to establish a new standard for patients and healthcare professionals seeking reliable medical information in the future [16][17][18].

Limitations
Of the responses generated by TGAI, 1.4% were deemed inappropriate which highlights the need for continuous training and refinement of the TGAI tools, as well as vigilance in ensuring the utilization of the current medical guidelines by TGAI software when generating responses.Though negligible, some TGAIgenerated responses were classified as unreliable, suggesting the need for further evaluation and improvement.Furthermore, there could be other questions that patients can ask on this topic that were not included in this study, necessitating further studies to ensure a comprehensive review of this topic.

Conclusions
TGAI offers medical information in terms of quality and reliability.Remarkably, this study highlights the notable efficacy of TGAI in delivering reliable and standard-compliant information on T2DM.An overwhelming 98.5% of responses rendered by the model were aligned with the standard of care, a statistic that holds promise for the advancing landscape of patient education and artificial intelligence.As with previous studies, these findings could pave the way for incorporating AI-based platforms as supplementary tools for enhancing patient understanding and improving outcomes.Thus, while TGAI demonstrates potential as a supplementary tool for diabetes education, it emphasizes that while technology can assist, human expertise is still necessary.The blend of both, when used judiciously, can help in a new era of informed patient-centric care.

FIGURE 1 :
FIGURE 1: Appropriateness of answers provided by ChatGPT for type 2 diabetes education.

TABLE 2 : Evaluation of ChatGPT recommendation for questions about diabetes prevention and screening based on assessment by Board-Certified Internal Medicine Physicians.
ChatGPT: Chat Generative Pre-trained Transformer; COVID: coronavirus disease 2019 al. (88%) [5], Ayers et al.where out of the 195 questions and responses, ChatBot (ChatGPT version 3.5; San Francisco, CA: OpenAI) responses were favored by evaluators over physician responses in 78.6% of cases [10], and Momenaei et al. (84.6%